Assessment of major solid wastes generated in palm oil mills
Two multivariate statistical techniques, viz. Discriminant Analysis (DA) and Principal Components Analysis (PCA) were used for the analysis of amount of solid wastes generated, such as Empty Fruit Bunches (EFB), potash ash, fibre and shell, in five different palm oil mills. DA identified two functions responsible for discriminating the mills on the basis of solid waste generated in these mills. It is observed that the differences between mills were mainly due to potash ash, EFB, and shell, affording 98.3% correct assignment. PCA identified only one component responsible for explaining 98.9% of the total variance in the data representing the average of selected parameters. This study narrows the pollution identification processes from huge data and identifies the major sources of pollution. This analysis is also helpful in the efficient management of solid wastes to reduce their impacts on the environment.
Keywords: solid waste, palm oil mills, discriminant analysis, principal component analysis, PCA, waste management, environmental pollution